Stroke is the third leading cause of death and the leading cause of disability in the United States. Previous studies have shown a link between social networks and social supports and all-cause mortality as well as to recovery from serious illness. While several studies of social integration and cardiovascular disease have been conducted, evidence regarding the role of social integration in stroke is rare and conflicted. It is plausible that the same mechanisms linking social integration and cardiovascular disease are also involved in stroke. Previous attempts to identify this link have suffered from poor measurement of social relationships, or from inadequate statistical power. The central aim of this research is to examine the impact of social networks and social support on several stroke outcomes including incidence, mortality, case fatality, functional recovery and discharge destination. Data from three large-scale prospective cohort studies and one psychosocial intervention study will be analyzed. The four studies are: 1) the New Haven site of the EPESE study (n = 2,182); 2) the Duke EPESE site (n = 4,163); 3) the Health Professionals Follow-up Study (n = 32,624); and 4) the Families in Recovery from Stroke trial (n = 290). The five hypotheses to be tested are: 1) higher levels of social support and stronger social networks are associated with lower risk of incidence stroke among community-dwelling adults; 2) stronger social networks are associated with a lower risk of stroke mortality among community-dwelling adults; 3) higher levels of social support and stronger social networks are associated with improved functional recovery after stroke; 4) higher levels of social support and stronger social networks are associated with lower risk of all cause mortality among those who have sustained a stroke and who are discharged alive; and 5) higher levels of social support and stronger social networks are associated with a lower risk of discharge to a skilled nursing facility for long-term placement. Fatal and non-fatal strokes will be confirmed by matching with medical records, the national death index, as well as HCFA Part A Medicare data. Data gathering activities ongoing in two of the studies (HPFS and FIRST) which will lead to enhanced statistical power. The main independent variable, available in all four studies, is the Berkman-Syme Social Network Index (SNI). A range of additional measures of social support and networks will be also be utilized. A variety of statistical models will be used including: 1) Cox proportional hazards model (hypotheses 1, 2, 4); 2) OLS autoregression models (hypothesis 3); and 3) polychotomous logistic regression (hypothesis 5). Data from each study will be analyzed separately. The investigators state that the strength of this study will be the availability of substantial numbers of stroke cases across multiple studies. They further state that the proposed research will be the most comprehensive study of social integration and stroke to date, and will yield both clinically and policy relevant results. They conclude that information about how the social context impacts the etiology and course of this prevalent disease will lead to low-cost intervention strategies.